Skip to main content
Glama

Attom

by io.github.pipeworx-io

Attom Property Search

attom_property_search
Read-onlyIdempotent

"Find houses / homes / properties / real estate for sale or owned in [ZIP]" / "search properties near [coords]" / "homes in [neighborhood]" — search US residential and commercial properties by ZIP or lat/lng radius with filters (beds, baths, year built, property type). Returns matching addresses and ATTOM property IDs. Use first when you need to find candidate addresses, then call attom_property_detail / attom_avm / attom_sales_history on the picks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
radiusNoSearch radius in miles (use with latitude/longitude)
_apiKeyYesATTOM API key
maxBedsNoMaximum number of bedrooms
minBedsNoMinimum number of bedrooms
latitudeNoLatitude for radius search (use with longitude and radius)
longitudeNoLongitude for radius search (use with latitude and radius)
postalCodeNoZIP/postal code to search in
maxYearBuiltNoMaximum year built
minYearBuiltNoMinimum year built
propertyTypeNoProperty type filter (e.g., "SFR", "CONDO", "APARTMENT")
maxBathsTotalNoMaximum total bathrooms
minBathsTotalNoMinimum total bathrooms

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds context about the return format (addresses and property IDs) but does not contradict annotations. It adds minor behavioral information beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured paragraph. It front-loads natural language examples, states the core function, and ends with usage guidance. Every sentence adds value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 12 parameters, full schema coverage, an output schema, and multiple sibling tools, the description adequately covers the main usage patterns (ZIP vs. radius search, filtering options, and follow-up workflow). It is complete for agent understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with each parameter described in the input schema. The description provides high-level context (search by ZIP or radius, filters) but does not add meaning beyond what the schema already provides, hence baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it searches US residential and commercial properties by ZIP or lat/lng radius with filters. It provides natural language examples like "Find houses / homes / properties..." and lists what it returns (addresses, ATTOM property IDs). It also explicitly differentiates from sibling tools by naming attom_property_detail, attom_avm, and attom_sales_history as follow-up calls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage guidance: "Use first when you need to find candidate addresses, then call attom_property_detail / attom_avm / attom_sales_history on the picks." This tells the agent when to use this tool versus the alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Attom toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.7/5.0
Disambiguation2/5

Several tools overlap heavily: ask_pipeworx_beta is explicitly identical to ask_pipeworx right now, and ask_pipeworx_grounded shares the same router. The universal ask_pipeworx router also subsumes many domain-specific tools (attom_*, entity_profile, etc.), making it unclear when to use the specialist tools versus the catch-all.

Naming Consistency3/5

All names are snake_case and mostly descriptive, but conventions vary: ask_* and attom_* prefixes coexist with bare verbs (remember, forget, subscribe), noun phrases (entity_profile, polymarket_edges), and adjective-prefixed names (recent_alerts, recent_changes). The pattern is readable but not uniform.

Tool Count2/5

39 tools is well over the 25+ threshold for a heavy surface, especially for a server named 'Attom' that also includes memory, subscriptions, feedback, npm scanning, and AI-visibility tools beyond real estate. Many tools could be consolidated (e.g., the three ask_pipeworx variants, the six polymarket tools).

Completeness4/5

The real estate domain is well covered (search, detail, AVM, rental AVM, sales history, trends, assessment, schools), and the broader data platform includes discovery, grounded answers, entity profiles, comparisons, claim validation, subscriptions, and memory. Minor gaps exist only around edge features like OAuth-gated subscription persistence.

Resources